GigaFrames: Large-Scale Surveillance and Computational Forensics
Agency:
If, on the one hand, surveillance cameras, increasingly available in large cities, provide a large amount of visual data, on the other hand, the analysis of these data becomes a great challenge when done manually. Consequently, the automatic processing of this data becomes essential in order to assist security agents in crime prevention (vigilance) and search for evidence in cases where crimes have already occurred (Computational Forensics). Therefore, the instant of occurrence of an event (for example, a crime) marks an important tangency between the two areas. GigaFrames focuses on the development of computer vision and machine learning techniques to perform environment monitoring and digital forensic analysis from large volumes of data captured through surveillance cameras.
Contributions generated from this research…
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Publications
Gabriel Resende Gonçalves; Matheus Alves Diniz; Rayson Laroca; David Menotti; William Robson Schwartz Real-time Automatic License Plate Recognition Through Deep Multi-Task Networks Inproceedings In: Conference on Graphic, Patterns and Images (SIBGRAPI), pp. 1-8, 2018. @inproceedings{Goncalves:2018:SIBGRAPI, title = {Real-time Automatic License Plate Recognition Through Deep Multi-Task Networks}, author = {Gabriel Resende Gonçalves and Matheus Alves Diniz and Rayson Laroca and David Menotti and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper.pdf}, year = {2018}, date = {2018-09-04}, booktitle = {Conference on Graphic, Patterns and Images (SIBGRAPI)}, pages = {1-8}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Carlos Antonio Caetano Junior; Jefersson A dos Santos; William Robson Schwartz Statistical Measures from Co-occurrence of Codewords for Action Recognition Inproceedings In: VISAPP 2018 - International Conference on Computer Vision Theory and Applications, pp. 1-8, 2018. @inproceedings{Caetano:2018:VISAPP, title = {Statistical Measures from Co-occurrence of Codewords for Action Recognition}, author = {Carlos Antonio Caetano Junior and Jefersson A dos Santos and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/VISAPP_2018_CarlosCaetano.pdf}, year = {2018}, date = {2018-01-27}, booktitle = {VISAPP 2018 - International Conference on Computer Vision Theory and Applications}, pages = {1-8}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Ricardo Barbosa Kloss; Artur Jordao; William Robson Schwartz Face Verification Strategies for Employing Deep Models Inproceedings In: 13th IEEE International Conference on Automatic Face & Gesture Recognition, pp. 258-262, 2018. @inproceedings{Kloss:2018:FG, title = {Face Verification Strategies for Employing Deep Models}, author = {Ricardo Barbosa Kloss and Artur Jordao and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/Face-Verification-Strategies-for-Employing-Deep-Models.pdf}, year = {2018}, date = {2018-01-01}, booktitle = {13th IEEE International Conference on Automatic Face & Gesture Recognition}, pages = {258-262}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Artur Jordao; Ricardo Barbosa Kloss; William Robson Schwartz Latent hypernet: Exploring all Layers from Convolutional Neural Networks Inproceedings In: IEEE International Joint Conference on Neural Networks (IJCNN), pp. 1-7, 2018. @inproceedings{Jordao:2018b:IJCNN, title = {Latent hypernet: Exploring all Layers from Convolutional Neural Networks}, author = {Artur Jordao and Ricardo Barbosa Kloss and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/Latent-HyperNet-Exploring-the-Layers.pdf}, year = {2018}, date = {2018-01-01}, booktitle = {IEEE International Joint Conference on Neural Networks (IJCNN)}, pages = {1-7}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Rensso Victor Hugo Mora Colque; Carlos Antonio Caetano Junior; Victor Hugo Cunha de Melo; Guillermo Camara Chavez; William Robson Schwartz Novel Anomalous Event Detection based on Human-object Interactions Inproceedings In: VISAPP 2018 - International Conference on Computer Vision Theory and Applications, pp. 1-8, 2018. @inproceedings{Colque:2018:VISAPP, title = {Novel Anomalous Event Detection based on Human-object Interactions}, author = {Rensso Victor Hugo Mora Colque and Carlos Antonio Caetano Junior and Victor Hugo Cunha de Melo and Guillermo Camara Chavez and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/VISAPP_2018_92.pdf}, year = {2018}, date = {2018-01-01}, booktitle = {VISAPP 2018 - International Conference on Computer Vision Theory and Applications}, pages = {1-8}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Igor Leonardo Oliveira Bastos; Victor Hugo Cunha de Melo; Gabriel Resende Gonçalves; William Robson Schwartz MORA: A Generative Approach to Extract Spatiotemporal Information Applied to Gesture Recognition Inproceedings In: 15th International Conference on Advanced Video and Signal-based Surveillance (AVSS), pp. 1-6, 2018. @inproceedings{Bastos:2018:AVSS, title = {MORA: A Generative Approach to Extract Spatiotemporal Information Applied to Gesture Recognition}, author = {Igor Leonardo Oliveira Bastos and Victor Hugo Cunha de Melo and Gabriel Resende Gonçalves and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/MORA_.pdf}, year = {2018}, date = {2018-01-01}, booktitle = {15th International Conference on Advanced Video and Signal-based Surveillance (AVSS)}, pages = {1-6}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Ricardo Barbosa Kloss; Artur Jordao; William Robson Schwartz Boosted Projection An Ensemble of Transformation Models Inproceedings In: 22nd Iberoamerican Congress on Pattern Recognition (CIARP), pp. 331-338, 2018. @inproceedings{Kloss:2018:CIARP, title = {Boosted Projection An Ensemble of Transformation Models}, author = {Ricardo Barbosa Kloss and Artur Jordao and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/Boosted-Projection-An-Ensemble-of-Transformation-Models.pdf}, year = {2018}, date = {2018-01-01}, booktitle = {22nd Iberoamerican Congress on Pattern Recognition (CIARP)}, pages = {331-338}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Renan Oliveira Reis; Igor Henrique Dias; William Robson Schwartz Neural network control for active cameras using master-slave setup Inproceedings In: International Conference on Advanced Video and Signal-based Surveillance (AVSS), pp. 1-6, 2018. @inproceedings{Reis:2018:AVSS, title = {Neural network control for active cameras using master-slave setup}, author = {Renan Oliveira Reis and Igor Henrique Dias and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/renan_avss_2018-1-1.pdf}, year = {2018}, date = {2018-01-01}, booktitle = {International Conference on Advanced Video and Signal-based Surveillance (AVSS)}, pages = {1-6}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Antonio Carlos Nazare Junior; Filipe Oliveira de Costa; William Robson Schwartz Content-Based Multi-Camera Video Alignment using Accelerometer Data Inproceedings In: Advanced Video and Signal Based Surveillance (AVSS), 2018 15th IEEE International Conference on, pp. 1-6, 2018. @inproceedings{Nazare:2018:AVSS, title = {Content-Based Multi-Camera Video Alignment using Accelerometer Data}, author = {Antonio Carlos Nazare Junior and Filipe Oliveira de Costa and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/2018_avss_svsync_camera_ready.pdf}, year = {2018}, date = {2018-01-01}, booktitle = {Advanced Video and Signal Based Surveillance (AVSS), 2018 15th IEEE International Conference on}, pages = {1-6}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Artur Jordao; Ricardo Kloss; Fernando Yamada; William Robson Schwartz Pruning Deep Neural Networks using Partial Least Squares Journal Article In: ArXiv e-prints, 2018. @article{Jordao:2018:arXivb, title = {Pruning Deep Neural Networks using Partial Least Squares}, author = {Artur Jordao and Ricardo Kloss and Fernando Yamada and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/03/1810.07610.pdf}, year = {2018}, date = {2018-01-01}, journal = {ArXiv e-prints}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Igor Leonardo Oliveira Bastos; Larissa Rocha Soares; William Robson Schwartz Pyramidal Zernike Over Time: A spatiotemporal feature descriptor based on Zernike Moments Inproceedings In: Iberoamerican Congress on Pattern Recognition (CIARP 2017), pp. 77-85, 2017. @inproceedings{Bastos:2017:CIARP, title = {Pyramidal Zernike Over Time: A spatiotemporal feature descriptor based on Zernike Moments}, author = {Igor Leonardo Oliveira Bastos and Larissa Rocha Soares and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/PZOT_camera_ready.pdf}, year = {2017}, date = {2017-11-07}, booktitle = {Iberoamerican Congress on Pattern Recognition (CIARP 2017)}, pages = {77-85}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Rensso Victor Hugo Mora Colque; Carlos Antonio Caetano Junior; Matheus Toledo Lustosa de Andrade; William Robson Schwartz Histograms of Optical Flow Orientation and Magnitude and Entropy to Detect Anomalous Events in Videos Journal Article In: IEEE Transactions on Circuits and Systems for Video Technology, 27 (3), pp. 673-682, 2017. @article{Colque:2016:TCSVT, title = {Histograms of Optical Flow Orientation and Magnitude and Entropy to Detect Anomalous Events in Videos}, author = {Rensso Victor Hugo Mora Colque and Carlos Antonio Caetano Junior and Matheus Toledo Lustosa de Andrade and William Robson Schwartz}, url = {http://dx.doi.org/10.1109/TCSVT.2016.2637778}, year = {2017}, date = {2017-01-01}, journal = {IEEE Transactions on Circuits and Systems for Video Technology}, volume = {27}, number = {3}, pages = {673-682}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Carlos Antonio Caetano Junior; Victor Hugo Cunha de Melo; Jefersson Alex dos Santos; William Robson Schwartz Activity Recognition based on a Magnitude-Orientation Stream Network Inproceedings In: Conference on Graphics, Patterns and Images (SIBGRAPI), pp. 1-8, 2017. @inproceedings{Caetano:2017:SIBGRAPI, title = {Activity Recognition based on a Magnitude-Orientation Stream Network}, author = {Carlos Antonio Caetano Junior and Victor Hugo Cunha de Melo and Jefersson Alex dos Santos and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2017_SIBGRAPI_Caetano.pdf}, year = {2017}, date = {2017-01-01}, booktitle = {Conference on Graphics, Patterns and Images (SIBGRAPI)}, pages = {1-8}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Artur Jordao; Jessica Sena; William Robson Schwartz A Late Fusion Approach to Combine Multiple Pedestrian Detectors Inproceedings In: IAPR International Conference on Pattern Recognition (ICPR), pp. 1-6, 2016. @inproceedings{Correia:2016:ICPR, title = {A Late Fusion Approach to Combine Multiple Pedestrian Detectors}, author = {Artur Jordao and Jessica Sena and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/A-Late-Fusion-Approach-to-Combine-Multiple.pdf}, year = {2016}, date = {2016-12-13}, booktitle = {IAPR International Conference on Pattern Recognition (ICPR)}, pages = {1-6}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Gabriel Resende Gonçalves; David Menotti; William Robson Schwartz License Plate Recognition based on Temporal Redundancy Inproceedings In: IEEE International Conference on Intelligent Transportation Systems (ITSC), pp. 1-5, 2016. @inproceedings{Goncalves:2016:ITSC, title = {License Plate Recognition based on Temporal Redundancy}, author = {Gabriel Resende Gonçalves and David Menotti and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2016_ITSC.pdf}, year = {2016}, date = {2016-11-04}, booktitle = {IEEE International Conference on Intelligent Transportation Systems (ITSC)}, pages = {1-5}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Gabriel Resende Gonçalves; Sirlene Pio Gomes da Silva; David Menotti; William Robson Schwartz Benchmark for License Plate Character Segmentation Journal Article In: Journal of Electronic Imaging, 25 (5), pp. 1-5, 2016, ISBN: 1017-9909. @article{2016:JEI:Gabriel, title = {Benchmark for License Plate Character Segmentation}, author = {Gabriel Resende Gonçalves and Sirlene Pio Gomes da Silva and David Menotti and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/JEI-2016-Benchmark.pdf}, isbn = {1017-9909}, year = {2016}, date = {2016-10-24}, journal = {Journal of Electronic Imaging}, volume = {25}, number = {5}, pages = {1-5}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Rafael Henrique Vareto; Filipe Oliveira de Costa; William Robson Schwartz Face Identification in Large Galleries Inproceedings In: Workshop on Face Processing Applications, pp. 1-4, 2016. @inproceedings{Vareto:2016:WFPA, title = {Face Identification in Large Galleries}, author = {Rafael Henrique Vareto and Filipe Oliveira de Costa and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2016_WFPA.pdf}, year = {2016}, date = {2016-10-02}, booktitle = {Workshop on Face Processing Applications}, pages = {1-4}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Raphael Felipe Carvalho de Prates; Cristianne Rodrigues Santos Dutra; William Robson Schwartz Predominant Color Name Indexing Structure for Person Re-Identification Inproceedings In: IEEE International Conference on Image Processing (ICIP), 2016. @inproceedings{Prates2016ICIP, title = {Predominant Color Name Indexing Structure for Person Re-Identification}, author = {Raphael Felipe Carvalho de Prates and Cristianne Rodrigues Santos Dutra and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2016_ICIP_Prates.pdf}, year = {2016}, date = {2016-09-25}, booktitle = {IEEE International Conference on Image Processing (ICIP)}, abstract = {The automation of surveillance systems is important to allow real-time analysis of critical events, crime investigation and prevention. A crucial step in the surveillance systems is the person re-identification (Re-ID) which aims at maintaining the identity of agents in non-overlapping camera networks. Most of the works in literature compare a test sample against the entire gallery, restricting the scalability. We address this problem employing multiple indexing lists obtained by color name descriptors extracted from partbased models using our proposed Predominant Color Name (PCN) indexing structure. PCN is a flexible indexing structure that relates features to gallery images without the need of labelled training images and can be integrated with existing supervised and unsupervised person Re-ID frameworks. Experimental results demonstrate that the proposed approach outperforms indexation based on unsupervised clustering methods such as k-means and c-means. Furthermore, PCN reduces the computational efforts with a minimum performance degradation. For instance, when indexing 50% and 75% of the gallery images, we observed a reduction in AUC curve of 0.01 and 0.08, respectively, when compared to indexing the entire gallery.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } The automation of surveillance systems is important to allow real-time analysis of critical events, crime investigation and prevention. A crucial step in the surveillance systems is the person re-identification (Re-ID) which aims at maintaining the identity of agents in non-overlapping camera networks. Most of the works in literature compare a test sample against the entire gallery, restricting the scalability. We address this problem employing multiple indexing lists obtained by color name descriptors extracted from partbased models using our proposed Predominant Color Name (PCN) indexing structure. PCN is a flexible indexing structure that relates features to gallery images without the need of labelled training images and can be integrated with existing supervised and unsupervised person Re-ID frameworks. Experimental results demonstrate that the proposed approach outperforms indexation based on unsupervised clustering methods such as k-means and c-means. Furthermore, PCN reduces the computational efforts with a minimum performance degradation. For instance, when indexing 50% and 75% of the gallery images, we observed a reduction in AUC curve of 0.01 and 0.08, respectively, when compared to indexing the entire gallery. |
Raphael Felipe Carvalho de Prates; Marina Santos Oliveira; William Robson Schwartz Kernel Partial Least Squares for Person Re-Identification Inproceedings In: IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), 2016. @inproceedings{Prates2016AVSS, title = {Kernel Partial Least Squares for Person Re-Identification}, author = {Raphael Felipe Carvalho de Prates and Marina Santos Oliveira and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/egpaper_for_DoubleBlindReview.pdf}, year = {2016}, date = {2016-09-25}, booktitle = {IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS)}, abstract = {Person re-identification (Re-ID) keeps the same identity for a person as he moves along an area with nonoverlapping surveillance cameras. Re-ID is a challenging task due to appearance changes caused by different camera viewpoints, occlusion and illumination conditions. While robust and discriminative descriptors are obtained combining texture, shape and color features in a high-dimensional representation, the achievement of accuracy and efficiency demands dimensionality reduction methods. At this paper, we propose variations of Kernel Partial Least Squares (KPLS) that simultaneously reduce the dimensionality and increase the discriminative power. The Cross-View KPLS (X-KPLS) and KPLS Mode A capture cross-view discriminative information and are successful for unsupervised and supervised Re-ID. Experimental results demonstrate that XKPLS presents equal or higher matching results when compared to other methods in literature at PRID450S.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Person re-identification (Re-ID) keeps the same identity for a person as he moves along an area with nonoverlapping surveillance cameras. Re-ID is a challenging task due to appearance changes caused by different camera viewpoints, occlusion and illumination conditions. While robust and discriminative descriptors are obtained combining texture, shape and color features in a high-dimensional representation, the achievement of accuracy and efficiency demands dimensionality reduction methods. At this paper, we propose variations of Kernel Partial Least Squares (KPLS) that simultaneously reduce the dimensionality and increase the discriminative power. The Cross-View KPLS (X-KPLS) and KPLS Mode A capture cross-view discriminative information and are successful for unsupervised and supervised Re-ID. Experimental results demonstrate that XKPLS presents equal or higher matching results when compared to other methods in literature at PRID450S. |
Gabriel Resende Goncalves License Plate Recognition based on Temporal Redundancy Masters Thesis Federal University of Minas Gerais, 2016. @mastersthesis{Goncalves:2016:MSc, title = {License Plate Recognition based on Temporal Redundancy}, author = {Gabriel Resende Goncalves}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/03/dissertation_2016_Gabriel.pdf}, year = {2016}, date = {2016-08-26}, school = {Federal University of Minas Gerais}, abstract = {Recognition of vehicle license plates is an important task applied to a myriad of real scenarios. Most approaches in the literature first detect an on-track vehicle, locate the license plate, perform a segmentation of its characters and then recognize the characters using an Optical Character Recognition (OCR) approach. However, these approaches focus on performing these tasks using only a single frame of each vehicle in the video. Therefore, such techniques might have their recognition rates reduced due to noise present in that particular frame. On the other hand, in this work we propose an approach to automatically detect the vehicle on the road and identify (locate/recognize) its license plate based on temporal redundant information instead of selecting a single frame to perform the recognition. We also propose two post-processing steps that can be employed to improve the accuracy of the system by querying a license plate database (e.g., the Department of Motor Vehicles database containing a list of all issued license plates and car models). Experimental results demonstrate that it is possible to improve the vehicle recognition rate in 15.5 percentage points (p.p.) (an increase of 23.38%) of the baseline results, using our proposal temporal redundancy approach. Furthermore, additional 7.8 p.p. are achieved using the two post-processing approaches, leading to a final recognition rate of 89.6% on a dataset with 5,200 frame images of $300$ vehicles recorded at Federal University of Minas Gerais (UFMG). In addition, this work also proposes a novel benchmark, designed specifically to evaluate character segmentation techniques, composed of a dataset of 2,000 Brazilian license plates (resulting in 14,000 alphanumeric symbols) and an evaluation protocol considering a novel evaluation measure, the Jaccard-Centroid coefficient.}, keywords = {}, pubstate = {published}, tppubtype = {mastersthesis} } Recognition of vehicle license plates is an important task applied to a myriad of real scenarios. Most approaches in the literature first detect an on-track vehicle, locate the license plate, perform a segmentation of its characters and then recognize the characters using an Optical Character Recognition (OCR) approach. However, these approaches focus on performing these tasks using only a single frame of each vehicle in the video. Therefore, such techniques might have their recognition rates reduced due to noise present in that particular frame. On the other hand, in this work we propose an approach to automatically detect the vehicle on the road and identify (locate/recognize) its license plate based on temporal redundant information instead of selecting a single frame to perform the recognition. We also propose two post-processing steps that can be employed to improve the accuracy of the system by querying a license plate database (e.g., the Department of Motor Vehicles database containing a list of all issued license plates and car models). Experimental results demonstrate that it is possible to improve the vehicle recognition rate in 15.5 percentage points (p.p.) (an increase of 23.38%) of the baseline results, using our proposal temporal redundancy approach. Furthermore, additional 7.8 p.p. are achieved using the two post-processing approaches, leading to a final recognition rate of 89.6% on a dataset with 5,200 frame images of $300$ vehicles recorded at Federal University of Minas Gerais (UFMG). In addition, this work also proposes a novel benchmark, designed specifically to evaluate character segmentation techniques, composed of a dataset of 2,000 Brazilian license plates (resulting in 14,000 alphanumeric symbols) and an evaluation protocol considering a novel evaluation measure, the Jaccard-Centroid coefficient. |
Artur Jordao The Good, the Fast and the Better Pedestrian Detector Masters Thesis Federal University of Minas Gerais, 2016. @mastersthesis{Jordao:2016:MSc, title = {The Good, the Fast and the Better Pedestrian Detector}, author = {Artur Jordao}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/03/dissertation_2016_ArturJordao.pdf}, year = {2016}, date = {2016-06-24}, school = {Federal University of Minas Gerais}, abstract = {Pedestrian detection is a well-known problem in Computer Vision, mostly because of its direct applications in surveillance, transit safety and robotics. In the past decade, several efforts have been performed to improve the detection in terms of accuracy, speed and feature enhancement. In this work, we propose and analyze techniques focusing on these points. First, we develop an accurate oblique random forest (oRF) associated with Partial Least Squares (PLS). The method utilizes the PLS to find a decision surface, at each node of a decision tree, that better splits the samples presented to it, based on some purity criterion. To measure the advantages provided by PLS on the oRF, we compare the proposed method with the oRF based on SVM. Second, we evaluate and compare filtering approaches to reduce the search space and keep only potential regions of interest to be presented to detectors, speeding up the detection process. Experimental results demonstrate that the evaluated filters are able to discard a large number of detection windows without compromising the accuracy. Finally, we propose a novel approach to extract powerful features regarding the scene. The method combines results of distinct pedestrian detectors by reinforcing the human hypothesis, whereas suppressing a significant number of false positives due to the lack of spatial consensus when multiple detectors are considered. Our proposed approach, referred to as Spatial Consensus (SC), outperforms all previously published state-of-the-art pedestrian detection methods.}, keywords = {}, pubstate = {published}, tppubtype = {mastersthesis} } Pedestrian detection is a well-known problem in Computer Vision, mostly because of its direct applications in surveillance, transit safety and robotics. In the past decade, several efforts have been performed to improve the detection in terms of accuracy, speed and feature enhancement. In this work, we propose and analyze techniques focusing on these points. First, we develop an accurate oblique random forest (oRF) associated with Partial Least Squares (PLS). The method utilizes the PLS to find a decision surface, at each node of a decision tree, that better splits the samples presented to it, based on some purity criterion. To measure the advantages provided by PLS on the oRF, we compare the proposed method with the oRF based on SVM. Second, we evaluate and compare filtering approaches to reduce the search space and keep only potential regions of interest to be presented to detectors, speeding up the detection process. Experimental results demonstrate that the evaluated filters are able to discard a large number of detection windows without compromising the accuracy. Finally, we propose a novel approach to extract powerful features regarding the scene. The method combines results of distinct pedestrian detectors by reinforcing the human hypothesis, whereas suppressing a significant number of false positives due to the lack of spatial consensus when multiple detectors are considered. Our proposed approach, referred to as Spatial Consensus (SC), outperforms all previously published state-of-the-art pedestrian detection methods. |
Cristianne Rodrigues Santos Dutra Técnicas Otimizadas para Reidentificaçâo de Pessoas Masters Thesis Federal University of Minas Gerais, 2016. @mastersthesis{Dutra:2016:MSc, title = {Técnicas Otimizadas para Reidentificaçâo de Pessoas}, author = {Cristianne Rodrigues Santos Dutra}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/thesis_2016_Cristianne.pdf}, year = {2016}, date = {2016-01-01}, school = {Federal University of Minas Gerais}, keywords = {}, pubstate = {published}, tppubtype = {mastersthesis} } |
Cassio Elias Santos dos Junior Partial Least Squares for Face Hashing Masters Thesis Federal University of Minas Gerais, 2015. @mastersthesis{Santos:2015:MSc, title = {Partial Least Squares for Face Hashing}, author = {Cassio Elias Santos dos Junior}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/dissertation_2015_Cassio.pdf}, year = {2015}, date = {2015-08-24}, school = {Federal University of Minas Gerais}, abstract = {Face identification is an important research topic due to areas such as its application to surveillance, forensics and human-computer interaction. In the past few years, a myriad of methods for face identification has been proposed in the literature, with just a few among them focusing on scalability. In this work, we propose a simple but efficient approach for scalable face identification based on partial least squares (PLS) and random independent hash functions inspired by locality-sensitive hashing (LSH), resulting in the PLS for hashing (PLSH) approach. The original PLSH approach is further extended using feature selection to reduce the computational cost to evaluate the PLS-based hash functions, resulting in the state-of-the-art extended PLSH approach (ePLSH). The proposed approach is evaluated in the dataset FERET and in the dataset FRGCv1. The results show significant reduction in the number of subjects evaluated in the face identification (reduced to 0.3% of the gallery), providing averaged speedups up to 233 times compared to evaluating all subjects in the face gallery and 58 times compared to previous works in the literature.}, keywords = {}, pubstate = {published}, tppubtype = {mastersthesis} } Face identification is an important research topic due to areas such as its application to surveillance, forensics and human-computer interaction. In the past few years, a myriad of methods for face identification has been proposed in the literature, with just a few among them focusing on scalability. In this work, we propose a simple but efficient approach for scalable face identification based on partial least squares (PLS) and random independent hash functions inspired by locality-sensitive hashing (LSH), resulting in the PLS for hashing (PLSH) approach. The original PLSH approach is further extended using feature selection to reduce the computational cost to evaluate the PLS-based hash functions, resulting in the state-of-the-art extended PLSH approach (ePLSH). The proposed approach is evaluated in the dataset FERET and in the dataset FRGCv1. The results show significant reduction in the number of subjects evaluated in the face identification (reduced to 0.3% of the gallery), providing averaged speedups up to 233 times compared to evaluating all subjects in the face gallery and 58 times compared to previous works in the literature. |
Cassio Elias Santos dos Junior; E Kijak; G Gravier; William Robson Schwartz Learning to Hash Faces Using Large Feature Vectors Inproceedings In: Content-Based Multimedia Indexing (CBMI), 13th International Workshop on, pp. 1–6, IEEE, 2015. @inproceedings{santos2015learning, title = {Learning to Hash Faces Using Large Feature Vectors}, author = {Cassio Elias Santos dos Junior and E Kijak and G Gravier and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/2015-Learning_to_Hash_Faces_Using_Large_Feature_Vectors.pdf}, year = {2015}, date = {2015-01-01}, booktitle = {Content-Based Multimedia Indexing (CBMI), 13th International Workshop on}, pages = {1--6}, publisher = {IEEE}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
A Pinto; H Pedrini; William Robson Schwartz; Rocha A Face Spoofing Detection Through Visual Codebooks of Spectral Temporal Cubes Journal Article In: Image Processing, IEEE Transactions on, 24 (12), pp. 4726-4740, 2015, ISSN: 1057-7149. @article{TIP:2015:Pinto, title = {Face Spoofing Detection Through Visual Codebooks of Spectral Temporal Cubes}, author = {A Pinto and H Pedrini and William Robson Schwartz and Rocha A}, url = {http://dx.doi.org/10.1109/TIP.2015.2466088}, issn = {1057-7149}, year = {2015}, date = {2015-01-01}, journal = {Image Processing, IEEE Transactions on}, volume = {24}, number = {12}, pages = {4726-4740}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Ramon F Pessoa; William Robson Schwartz; Jefersson A dos Santos A Study on Low-Cost Representations for Image Feature Extraction on Mobile Devices Inproceedings In: 14th Iberoamerican Congress on Pattern Recognition (CIARP), pp. 1-8, 2015. @inproceedings{Pessoa:2015:CIARP, title = {A Study on Low-Cost Representations for Image Feature Extraction on Mobile Devices}, author = {Ramon F Pessoa and William Robson Schwartz and Jefersson A dos Santos}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2015_CIARP_Pessoa.pdf}, year = {2015}, date = {2015-01-01}, booktitle = {14th Iberoamerican Congress on Pattern Recognition (CIARP)}, pages = {1-8}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Raphael Felipe Carvalho de Prates; William Robson Schwartz CBRA: Color-Based Ranking Aggregation for Person Re-Identification Inproceedings In: IEEE International Conference on Image Processing (ICIP), pp. 1-5, 2015. @inproceedings{Prates:2015:ICB, title = {CBRA: Color-Based Ranking Aggregation for Person Re-Identification}, author = {Raphael Felipe Carvalho de Prates and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2015_ICIP_Prates.pdf}, year = {2015}, date = {2015-01-01}, booktitle = {IEEE International Conference on Image Processing (ICIP)}, pages = {1-5}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |